added evergreen and angio plus global standardization

Makefile

@@ -27,7 +27,7 @@ $(D2)/TRY/data.TRY.std.rds:
 BCI: $(D3)/BCI/Done.txt
 
 $(D3)/BCI/Done.txt: R/process.data/process.fun.R $(D2)/BCI/traits.csv
-	Rscript -e "source('$<'); process_bigplot_dataset('BCI', Rlim=15); process_bigplot_dataset('BCI', Rlim=15,std.traits=FALSE);"
+	Rscript -e "source('$<'); process_bigplot_dataset('BCI', Rlim=15,std.traits='local'); process_bigplot_dataset('BCI', Rlim=15,std.traits='no'); process_bigplot_dataset('BCI', Rlim=15,std.traits='global');"
 
 $(D2)/BCI/traits.csv: R/find.trait/BCI.R R/find.trait/trait.fun.R $(D2)/BCI/tree.csv $(D2)/TRY/data.TRY.std.rds
 	Rscript $<
@@ -40,7 +40,7 @@ $(D2)/BCI/tree.csv: R/format.data/BCI.R $(shell find $(D1)/BCI -type f)
 Japan: $(D3)/Japan/Done.txt
 
 $(D3)/Japan/Done.txt: R/process.data/process.fun.R $(D2)/Japan/traits.csv
-	Rscript -e "source('$<'); process_bigplot_dataset('Japan', Rlim=15);  process_bigplot_dataset('Japan', Rlim=15,std.traits=FALSE);"
+	Rscript -e "source('$<'); process_bigplot_dataset('Japan', Rlim=15,std.traits='local');  process_bigplot_dataset('Japan', Rlim=15,std.traits='no'); process_bigplot_dataset('Japan', Rlim=15,std.traits='global');"
 
 $(D2)/Japan/traits.csv: R/find.trait/Japan.R R/find.trait/trait.fun.R $(D2)/Japan/tree.csv $(D2)/TRY/data.TRY.std.rds
 	Rscript $<
@@ -52,7 +52,7 @@ $(D2)/Japan/tree.csv: R/format.data/Japan.R $(shell find $(D1)/Japan -type f)
 Luquillo: $(D3)/Luquillo/Done.txt
 
 $(D3)/Luquillo/Done.txt: R/process.data/process.fun.R $(D2)/Luquillo/traits.csv
-	Rscript -e "source('$<'); process_bigplot_dataset('Luquillo', Rlim=15);  process_bigplot_dataset('Luquillo', Rlim=15,std.traits=FALSE);"
+	Rscript -e "source('$<'); process_bigplot_dataset('Luquillo', Rlim=15,std.traits='local');  process_bigplot_dataset('Luquillo', Rlim=15,std.traits='no');process_bigplot_dataset('Luquillo', Rlim=15,std.traits='global');"
 
 $(D2)/Luquillo/traits.csv: R/find.trait/Luquillo.R R/find.trait/trait.fun.R $(D2)/Luquillo/tree.csv $(D2)/TRY/data.TRY.std.rds
 	Rscript $<
@@ -65,7 +65,7 @@ $(D2)/Luquillo/tree.csv: R/format.data/Luquillo.R $(shell find $(D1)/Luquillo -t
 Mbaiki: $(D3)/Mbaiki/Done.txt
 
 $(D3)/Mbaiki/Done.txt: R/process.data/process.fun.R $(D2)/Mbaiki/traits.csv
-	Rscript -e "source('$<'); process_bigplot_dataset('Mbaiki', Rlim=15); process_bigplot_dataset('Mbaiki', Rlim=15,std.traits=FALSE);"
+	Rscript -e "source('$<'); process_bigplot_dataset('Mbaiki', Rlim=15,std.traits='local'); process_bigplot_dataset('Mbaiki', Rlim=15,std.traits='no'); process_bigplot_dataset('Mbaiki', Rlim=15,std.traits='global');"
 
 $(D2)/Mbaiki/traits.csv: R/find.trait/Mbaiki.R R/find.trait/trait.fun.R $(D2)/Mbaiki/tree.csv $(D2)/TRY/data.TRY.std.rds
 	Rscript $<
@@ -78,7 +78,7 @@ $(D2)/Mbaiki/tree.csv: R/format.data/Mbaiki.R $(shell find $(D1)/Mbaiki -type f)
 Canada: $(D3)/Canada/Done.txt
 
 $(D3)/Canada/Done.txt: R/process.data/process.fun.R  $(D2)/Canada/traits.csv
-	Rscript -e "source('$<'); process_inventory_dataset('Canada'); process_inventory_dataset('Canada',std.traits=FALSE);"
+	Rscript -e "source('$<'); process_inventory_dataset('Canada',std.traits='local'); process_inventory_dataset('Canada',std.traits='no');process_inventory_dataset('Canada',std.traits='global');"
 
 $(D2)/Canada/traits.csv: R/find.trait/Canada.R R/find.trait/trait.fun.R $(D2)/Canada/tree.csv $(D2)/TRY/data.TRY.std.rds
 	Rscript $<
@@ -90,7 +90,7 @@ $(D2)/Canada/tree.csv: R/format.data/Canada.R $(shell find $(D1)/Canada -type f)
 France: $(D3)/France/Done.txt
 
 $(D3)/France/Done.txt: R/process.data/process.fun.R $(D2)/France/traits.csv
-	Rscript -e "source('$<'); process_inventory_dataset('France'); process_inventory_dataset('France',std.traits=FALSE);"
+	Rscript -e "source('$<'); process_inventory_dataset('France',std.traits='local'); process_inventory_dataset('France',std.traits='no');process_inventory_dataset('France',std.traits='global');"
 
 $(D2)/France/traits.csv: R/find.trait/France.R R/find.trait/trait.fun.R $(D2)/France/tree.csv $(D2)/TRY/data.TRY.std.rds
 	Rscript $<
@@ -103,7 +103,7 @@ $(D2)/France/tree.csv: R/format.data/France.R $(shell find $(D1)/France -type f)
 Fushan: $(D3)/Fushan/Done.txt
 
 $(D3)/Fushan/Done.txt: R/process.data/process.fun.R $(D2)/Fushan/traits.csv
-	Rscript -e "source('$<'); process_bigplot_dataset('Fushan', Rlim=15); process_bigplot_dataset('Fushan', Rlim=15,std.traits=FALSE);"
+	Rscript -e "source('$<'); process_bigplot_dataset('Fushan', Rlim=15,std.traits='local'); process_bigplot_dataset('Fushan', Rlim=15,std.traits='no');process_bigplot_dataset('Fushan', Rlim=15,std.traits='global');"
 
 
 $(D2)/Fushan/traits.csv: R/find.trait/Fushan.R R/find.trait/trait.fun.R $(D2)/Fushan/tree.csv $(D2)/TRY/data.TRY.std.rds
@@ -117,7 +117,7 @@ $(D2)/Fushan/tree.csv: R/format.data/Fushan.R $(shell find $(D1)/Fushan -type f)
 NSW: $(D3)/NSW/Done.txt
 
 $(D3)/NSW/Done.txt: R/process.data/process.fun.R $(D2)/NSW/traits.csv
-	Rscript -e "source('$<'); process_inventory_dataset('NSW');  process_inventory_dataset('NSW',std.traits=FALSE);"
+	Rscript -e "source('$<'); process_inventory_dataset('NSW',std.traits='local');  process_inventory_dataset('NSW',std.traits='no');process_inventory_dataset('NSW',std.traits='global');"
 
 $(D2)/NSW/traits.csv: R/find.trait/NSW.R R/find.trait/trait.fun.R $(D2)/NSW/tree.csv $(D2)/TRY/data.TRY.std.rds
 	Rscript $<
@@ -130,7 +130,7 @@ $(D2)/NSW/tree.csv: R/format.data/NSW.R $(shell find $(D1)/NSW -type f)
 NVS: $(D3)/NVS/Done.txt
 
 $(D3)/NVS/Done.txt: R/process.data/process.fun.R $(D2)/NVS/traits.csv
-	Rscript -e "source('$<'); process_inventory_dataset('NVS');  process_inventory_dataset('NVS',std.traits=FALSE);"
+	Rscript -e "source('$<'); process_inventory_dataset('NVS',std.traits='local');  process_inventory_dataset('NVS',std.traits='no'); process_inventory_dataset('NVS',std.traits='global');"
 
 $(D2)/NVS/traits.csv: R/find.trait/NVS.R R/find.trait/trait.fun.R $(D2)/NVS/tree.csv $(D2)/TRY/data.TRY.std.rds
 	Rscript $<
@@ -143,7 +143,7 @@ $(D2)/NVS/tree.csv: R/format.data/NVS.R $(shell find $(D1)/NVS -type f)
 Paracou: $(D3)/Paracou/Done.txt
 
 $(D3)/Paracou/Done.txt: R/process.data/process.fun.R $(D2)/Paracou/traits.csv
-	Rscript -e "source('$<'); process_bigplot_dataset('Paracou', Rlim=15);  process_bigplot_dataset('Paracou', Rlim=15,std.traits=FALSE);"
+	Rscript -e "source('$<'); process_bigplot_dataset('Paracou', Rlim=15,std.traits='local');  process_bigplot_dataset('Paracou', Rlim=15,std.traits='no');  process_bigplot_dataset('Paracou', Rlim=15,std.traits='global');"
 
 $(D2)/Paracou/traits.csv: R/find.trait/Paracou.R R/find.trait/trait.fun.R $(D2)/Paracou/tree.csv $(D2)/TRY/data.TRY.std.rds
 	Rscript $<
@@ -156,7 +156,7 @@ $(D2)/Paracou/tree.csv: R/format.data/Paracou.R $(shell find $(D1)/Paracou -type
 Spain: $(D3)/Spain/Done.txt
 
 $(D3)/Spain/Done.txt: R/process.data/process.fun.R $(D2)/Spain/traits.csv
-	Rscript -e "source('$<'); process_inventory_dataset('Spain');  process_inventory_dataset('Spain',std.traits=FALSE);"
+	Rscript -e "source('$<'); process_inventory_dataset('Spain',std.traits='local');  process_inventory_dataset('Spain',std.traits='no'); process_inventory_dataset('Spain',std.traits='global');"
 
 $(D2)/Spain/traits.csv: R/find.trait/Spain.R R/find.trait/trait.fun.R $(D2)/Spain/tree.csv $(D2)/TRY/data.TRY.std.rds
 	Rscript $<
@@ -169,7 +169,7 @@ $(D2)/Spain/tree.csv: R/format.data/Spain.R $(shell find $(D1)/Spain -type f)
 Sweden: $(D3)/Sweden/Done.txt
 
 $(D3)/Sweden/Done.txt: R/process.data/process.fun.R  $(D2)/Sweden/traits.csv
-	Rscript -e "source('$<'); process_inventory_dataset('Sweden');  process_inventory_dataset('Sweden',std.traits=FALSE);"
+	Rscript -e "source('$<'); process_inventory_dataset('Sweden',std.traits='local');  process_inventory_dataset('Sweden',std.traits='no'); process_inventory_dataset('Sweden',std.traits='global');"
 
 $(D2)/Sweden/traits.csv: R/find.trait/Sweden.R R/find.trait/trait.fun.R $(D2)/Sweden/tree.csv $(D2)/TRY/data.TRY.std.rds
 	Rscript $<
@@ -182,7 +182,7 @@ $(D2)/Sweden/tree.csv: R/format.data/Sweden.R $(shell find $(D1)/Sweden -type f)
 Swiss: $(D3)/Swiss/Done.txt
 
 $(D3)/Swiss/Done.txt: R/process.data/process.fun.R $(D2)/Swiss/traits.csv
-	Rscript -e "source('$<'); process_inventory_dataset('Swiss');  process_inventory_dataset('Swiss',std.traits=FALSE);"
+	Rscript -e "source('$<'); process_inventory_dataset('Swiss',std.traits='local');  process_inventory_dataset('Swiss',std.traits='no'); process_inventory_dataset('Swiss',std.traits='global');"
 
 $(D2)/Swiss/traits.csv: R/find.trait/Swiss.R R/find.trait/trait.fun.R $(D2)/Swiss/tree.csv $(D2)/TRY/data.TRY.std.rds
 	Rscript $<
@@ -195,7 +195,7 @@ $(D2)/Swiss/tree.csv: R/format.data/Swiss.R $(shell find $(D1)/Swiss -type f)
 US: $(D3)/US/Done.txt
 
 $(D3)/US/Done.txt: R/process.data/process.fun.R  $(D2)/US/traits.csv
-	Rscript -e "source('$<'); process_inventory_dataset('US'); process_inventory_dataset('US',std.traits=FALSE);"
+	Rscript -e "source('$<'); process_inventory_dataset('US',std.traits='local'); process_inventory_dataset('US',std.traits='no');process_inventory_dataset('US',std.traits='global');"
 
 $(D2)/US/traits.csv: R/find.trait/US.R R/find.trait/trait.fun.R $(D2)/US/tree.csv $(D2)/TRY/data.TRY.std.rds
 	Rscript $<

R/analysis/lmer.nolog.output.R

@@ -13,7 +13,7 @@ for (set in sets){
 ecoregions <- get.ecoregions.for.set(set)
     for (ecoregion in ecoregions){
       for (trait in traits){
-          for (model in c(model.files.lmer.Tf.1)){
+          for (model in c(model.files.lmer.Tf.1,model.files.lmer.Tf.2)){
        source(model, local = TRUE)
        model.obj <- load.model()
 

R/analysis/lmer.output-fun.R

@@ -396,9 +396,9 @@ fun.plot.panel.lmer.parameters.c <- function(models,traits,DF.results,var.x,list
                 mtext(var.x, side=1, line =4)
             if(j==1)
                 mtext(paste('param',names(models)[i]), side=2, line =4,cex=1)
-            if(i==nrows & j==ncols)
-                legend('topright',legend=levels(DF.results$set),pch=16,
-                       col=col.vec,bty='n',ncol=2)
+            ## if(i==nrows & j==ncols)
+            ##     legend('topright',legend=levels(DF.results$set),pch=16,
+            ##            col=col.vec,bty='n',ncol=2)
         }
 }
 

R/analysis/lmer.output.figs.R

@@ -49,6 +49,8 @@ DF.results <- cbind(DF.results,DF.R2m.diff,DF.R2c.diff,DF.AIC.diff,DF.delta.AIC,
 DF.best.and.all.AIC <- do.call('rbind',lapply(unique(DF.results$id2),FUN=fun.AIC,DF.results))
 DF.best.and.all.AICc <- do.call('rbind',lapply(unique(DF.results$id2),FUN=fun.AICc,DF.results))
 
+table(DF.best.and.all.AIC[DF.best.and.all.AIC$filling=='species',]$best.model)
+
 table(DF.best.and.all.AIC[DF.best.and.all.AIC$filling=='species',]$best.model,
       DF.best.and.all.AIC[DF.best.and.all.AIC$filling=='species',]$trait,
       DF.best.and.all.AIC[DF.best.and.all.AIC$filling=='species',]$set)
@@ -219,7 +221,8 @@ pdf('figs/parameters.MAP.ER.all.pdf',width=9,height=7)
 fun.plot.panel.lmer.parameters.c(models=models,
                                traits = c('Wood.density','SLA','Leaf.N','Max.height'),
                                DF.results,var.x='MAP',
-                               list.params=list.params,small.bar=0.02,ylim=c(-.15,.25),threshold.delta.AIC=10000)
+                               list.params=list.params,small.bar=0.02,
+                                 threshold.delta.AIC=10000)
 dev.off()
 
 models <- c('lmer.LOGLIN.ER.Tf','lmer.LOGLIN.ER.Tf')

R/analysis/run.local.R

 ##### SCRIPT TO TEST BEFORE TO SEND ON CLUSTER
 source("R/analysis/lmer.run.nolog.R")
 
-run.models.for.set.all.traits('France',model.files.lmer.Tf.1, run.lmer,type.filling='species',std=TRUE)
-run.models.for.set.all.traits('Spain',model.files.lmer.Tf.1, run.lmer,type.filling='species',std=TRUE)
-run.models.for.set.all.traits('Sweden',model.files.lmer.Tf.1, run.lmer,type.filling='species',std=TRUE)
-run.models.for.set.all.traits('Swiss',model.files.lmer.Tf.1, run.lmer,type.filling='species',std=TRUE)
-run.models.for.set.all.traits('BCI',model.files.lmer.Tf.1, run.lmer,type.filling='species',std=TRUE)
-run.models.for.set.all.traits('Fushan',model.files.lmer.Tf.1, run.lmer,type.filling='species',std=TRUE)
-run.models.for.set.all.traits('Luquillo',model.files.lmer.Tf.1, run.lmer,type.filling='species',std=TRUE)
-run.models.for.set.all.traits('NVS',model.files.lmer.Tf.1, run.lmer,type.filling='species',std=TRUE)
-run.models.for.set.all.traits('Japan',model.files.lmer.Tf.1, run.lmer,type.filling='species',std=TRUE)
-run.models.for.set.all.traits('Canada',model.files.lmer.Tf.1, run.lmer,type.filling='species',std=TRUE)
-run.models.for.set.all.traits('Paracou',model.files.lmer.Tf.1, run.lmer,type.filling='species',std=TRUE)
-run.models.for.set.all.traits('Mbaiki',model.files.lmer.Tf.1, run.lmer,type.filling='species',std=TRUE)
-run.models.for.set.all.traits('US',model.files.lmer.Tf.1, run.lmer,type.filling='species',std=TRUE)
 
 sets <- c('France','Spain','Sweden','Swiss','BCI','Fushan','Luquillo','NVS','Japan','Canada','Paracou','Mbaiki','US')
 library(doParallel)

R/find.trait/BCI.R

@@ -64,6 +64,26 @@ data.traits <- fun.extract.format.sp.traits.NOT.TRY(sp=species.clean$Latin_name,
 ## change sp
 data.traits$sp <- species.clean$sp
 
+
+
+#### GET THE ANGIO/CONIF AND EVERGREEN/DECIDUOUS
+# read try categrocial data
+try.cat <- read.csv("data/raw/TRY/TRY_Categorical_Traits_Lookup_Table_2012_03_17_TestRelease.csv",
+         stringsAsFactors=FALSE,na.strings = "")
+Pheno.Zanne <- read.csv("data/raw/ZanneNature/GlobalLeafPhenologyDatabase.csv",
+         stringsAsFactors=FALSE)
+# extract
+data.cat.extract <- do.call("rbind",lapply(data.traits$sp ,fun.get.cat.var.from.try,
+                                           data.traits,try.cat,Pheno.Zanne))
+# change category
+data.cat.extract <- fun.change.factor.pheno.try(data.cat.extract)
+data.cat.extract <- fun.change.factor.angio.try(data.cat.extract)
+data.cat.extract <- fun.fill.pheno.try.with.zanne(data.cat.extract)
+
+
+data.traits <- merge(data.traits,data.cat.extract[,c("sp","Phylo.group","Pheno.T")],by="sp")
+
+
 ### 
 write.csv(data.traits,file="output/formatted/BCI/traits.csv",row.names = FALSE)
 

R/find.trait/Canada.R

@@ -36,6 +36,28 @@ data.traits[is.na(data.traits[["Max.height.mean"]]),
             c("Max.height.mean","Max.height.sd","Max.height.genus")] <- height.genus.DF[
                                                                 is.na(data.traits[["Max.height.mean"]]),]
 
+#### GET THE ANGIO/CONIF AND EVERGREEN/DECIDUOUS
+# read try categrocial data
+try.cat <- read.csv("data/raw/TRY/TRY_Categorical_Traits_Lookup_Table_2012_03_17_TestRelease.csv",
+         stringsAsFactors=FALSE,na.strings = "")
+Pheno.Zanne <- read.csv("data/raw/ZanneNature/GlobalLeafPhenologyDatabase.csv",
+         stringsAsFactors=FALSE)
+# extract
+data.cat.extract <- do.call("rbind",lapply(data.traits$sp ,fun.get.cat.var.from.try,
+                                           data.traits,try.cat,Pheno.Zanne))
+# change category
+data.cat.extract <- fun.change.factor.pheno.try(data.cat.extract)
+data.cat.extract <- fun.change.factor.angio.try(data.cat.extract)
+data.cat.extract <- fun.fill.pheno.try.with.zanne(data.cat.extract)
+
+## fix pheno for species with issue
+data.cat.extract[data.cat.extract$Latin_name %in% c('Betula spp.','Crataegus spp.','Fraxinus spp.'
+                                                   ,'Malus spp.','Amelanchier spp.','Alnus spp.',
+                                                    'Tilia spp.','Ulmus spp.'),'Pheno.T'] <- 'D'
+
+
+data.traits <- merge(data.traits,data.cat.extract[,c("sp","Phylo.group","Pheno.T")],by="sp")
+
 ### 
 write.csv(data.traits,file="output/formatted/Canada/traits.csv",row.names = FALSE)
 

R/find.trait/France.R

@@ -37,30 +37,34 @@ data.traits[is.na(data.traits[["Max.height.mean"]]),
             height.genus.DF[is.na(data.traits[["Max.height.mean"]]),]
 
 
-#### TODO GET THE ANGIO/CONIF AND EVERGREEN/DECIDUOUS
-
+#### GET THE ANGIO/CONIF AND EVERGREEN/DECIDUOUS
 # read try categrocial data
 try.cat <- read.csv("data/raw/TRY/TRY_Categorical_Traits_Lookup_Table_2012_03_17_TestRelease.csv",
          stringsAsFactors=FALSE,na.strings = "")
 Pheno.Zanne <- read.csv("data/raw/ZanneNature/GlobalLeafPhenologyDatabase.csv",
          stringsAsFactors=FALSE)
+# extract
 data.cat.extract <- do.call("rbind",lapply(data.traits$sp ,fun.get.cat.var.from.try,
                                            data.traits,try.cat,Pheno.Zanne))
+# change category
+data.cat.extract <- fun.change.factor.pheno.try(data.cat.extract)
+data.cat.extract <- fun.change.factor.angio.try(data.cat.extract)
+data.cat.extract <- fun.fill.pheno.try.with.zanne(data.cat.extract)
+
+## fix pheno for species with issue
+data.cat.extract[data.cat.extract$Latin_name %in% c('Populus sp','Tilia europaea',
+                                                    'Prunus sp','Prunus dulcis',
+                                                    'Sorbus latifolia','Pyrus spinosa',
+                                                    'Sorbus semiincisa','Alnus alnobetula',
+                                                    'Crataegus azarolus','Frangula dodonei',
+                                                    'Tamarix africana'),'Pheno.T'] <- 'D'
 
-data.cat.extract[data.cat.extract$Pheno.T=='deciduous'
-                 & !is.na(data.cat.extract$Pheno.T),'Pheno.T'] <- 'D'
-data.cat.extract[data.cat.extract$Pheno.T=='evergreen'
-                 & !is.na(data.cat.extract$Pheno.T),'Pheno.T'] <- 'EV'
-data.cat.extract[data.cat.extract$Pheno.T=='deciduous/evergreen'
-                 & !is.na(data.cat.extract$Pheno.T),'Pheno.T'] <- 'D_EV'
+data.cat.extract[data.cat.extract$Latin_name %in% c('Pinus nigra spp. salzmannii')
+                 ,'Pheno.T']<-  'EV'
 
-data.traits <- merge(data.traits,data.cat.extract,by="sp")
 
-## check if leaf Phenology agree with Zanne
-sum(Pheno.Zanne$Binomial %in%  try.cat$AccSpeciesName)
-merge.pheno <- merge(Pheno.Zanne,try.cat,by.x="Binomial",by.y="AccSpeciesName",all=FALSE)
 
-table(merge.pheno$LeafPhenology,merge.pheno$Phenology)
+data.traits <- merge(data.traits,data.cat.extract[,c("sp","Phylo.group","Pheno.T")],by="sp")
 
 ### 
 write.csv(data.traits,file="output/formatted/France/traits.csv",row.names = FALSE)

R/find.trait/Fushan.R

@@ -36,7 +36,28 @@ rm(data.trait)
 
 ## extract
 data.traits <- fun.extract.format.sp.traits.NOT.TRY(sp=species.clean$sp, Latin_name=species.clean$sp, data=data.TRAITS.std,name.match.traits="sp")
-## Check heights here; we DO NOT want to take logs of max height!
+
+#### GET THE ANGIO/CONIF AND EVERGREEN/DECIDUOUS
+# TODO ASK SPECIES NAME OR EVERGREEN DECIDUOUS BECAUSE NO SPECIES NAME AVAILABLE
+
+#### GET THE ANGIO/CONIF AND EVERGREEN/DECIDUOUS
+# read try categrocial data
+try.cat <- read.csv("data/raw/TRY/TRY_Categorical_Traits_Lookup_Table_2012_03_17_TestRelease.csv",
+         stringsAsFactors=FALSE,na.strings = "")
+Pheno.Zanne <- read.csv("data/raw/ZanneNature/GlobalLeafPhenologyDatabase.csv",
+         stringsAsFactors=FALSE)
+# extract
+data.cat.extract <- do.call("rbind",lapply(data.traits$sp ,fun.get.cat.var.from.try,
+                                           data.traits,try.cat,Pheno.Zanne))
+# change category
+data.cat.extract <- fun.change.factor.pheno.try(data.cat.extract)
+data.cat.extract <- fun.change.factor.angio.try(data.cat.extract)
+data.cat.extract <- fun.fill.pheno.try.with.zanne(data.cat.extract)
+
+
+data.traits <- merge(data.traits,data.cat.extract[,c("sp","Phylo.group","Pheno.T")],by="sp")
+
+
 
 ### 
 write.csv(data.traits,file="output/formatted/Fushan/traits.csv",row.names = FALSE)

R/find.trait/Japan.R

@@ -42,6 +42,24 @@ data.trait$Max.height.sd <- NA
 ## read traits from TRY
 data.traits <- fun.extract.format.sp.traits.NOT.TRY(sp=species.clean$sp, Latin_name=species.clean$Latin_name, data=data.trait, name.match.traits="Latin_name")
 
+
+#### GET THE ANGIO/CONIF AND EVERGREEN/DECIDUOUS
+# read try categrocial data
+try.cat <- read.csv("data/raw/TRY/TRY_Categorical_Traits_Lookup_Table_2012_03_17_TestRelease.csv",
+         stringsAsFactors=FALSE,na.strings = "")
+Pheno.Zanne <- read.csv("data/raw/ZanneNature/GlobalLeafPhenologyDatabase.csv",
+         stringsAsFactors=FALSE)
+# extract
+data.cat.extract <- do.call("rbind",lapply(data.traits$sp ,fun.get.cat.var.from.try,
+                                           data.traits,try.cat,Pheno.Zanne))
+# change category
+data.cat.extract <- fun.change.factor.pheno.try(data.cat.extract)
+data.cat.extract <- fun.change.factor.angio.try(data.cat.extract)
+data.cat.extract <- fun.fill.pheno.try.with.zanne(data.cat.extract)
+
+
+data.traits <- merge(data.traits,data.cat.extract[,c("sp","Phylo.group","Pheno.T")],by="sp")
+
 ### TODO ADD GENUS MEAN FOR HEIGHT IF SPECIES IS MISSING
 write.csv(data.traits,file="output/formatted/Japan/traits.csv",row.names = FALSE)
 

R/find.trait/Luquillo.R

@@ -71,6 +71,34 @@ data.traits <- fun.extract.format.sp.traits.NOT.TRY(sp=species.clean$Latin_name,
 ## change sp
 data.traits$sp <- species.clean$sp
 
+
+#### GET THE ANGIO/CONIF AND EVERGREEN/DECIDUOUS
+# read try categrocial data
+try.cat <- read.csv("data/raw/TRY/TRY_Categorical_Traits_Lookup_Table_2012_03_17_TestRelease.csv",
+         stringsAsFactors=FALSE,na.strings = "")
+Pheno.Zanne <- read.csv("data/raw/ZanneNature/GlobalLeafPhenologyDatabase.csv",
+         stringsAsFactors=FALSE)
+# extract
+data.cat.extract <- do.call("rbind",lapply(data.traits$sp ,fun.get.cat.var.from.try,
+                                           data.traits,try.cat,Pheno.Zanne))
+# change category
+data.cat.extract <- fun.change.factor.pheno.try(data.cat.extract)
+data.cat.extract <- fun.change.factor.angio.try(data.cat.extract)
+data.cat.extract <- fun.fill.pheno.try.with.zanne(data.cat.extract)
+
+## fix pheno for species with issue
+data.cat.extract[data.cat.extract$Latin_name %in% c('Prestoea acuminata',
+                                                    'Matayba domingensis'),'Pheno.T'] <- 'D'
+
+data.cat.extract[data.cat.extract$Latin_name %in% c('Cecropia schreberiana',
+                                                    'Talipariti tiliaceum',
+                                                    'Eugenia domingensis',
+                                                    'Ficus crassinervia') ,'Pheno.T']<-  'EV'
+data.cat.extract[data.cat.extract$Latin_name %in% c('Chione venosa') ,'Pheno.T']<-  'D_EV'
+
+
+data.traits <- merge(data.traits,data.cat.extract[,c("sp","Phylo.group","Pheno.T")],by="sp")
+
 ### 
 write.csv(data.traits,file="output/formatted/Luquillo/traits.csv",row.names = FALSE)
 

R/find.trait/Mbaiki.R

@@ -157,6 +157,23 @@ data.traits <- fun.extract.format.sp.traits.NOT.TRY(sp=species.clean$Latin_name,
 ## change sp
 data.traits$sp <- species.clean$sp
 
+
+#### GET THE ANGIO/CONIF AND EVERGREEN/DECIDUOUS
+# read try categrocial data
+try.cat <- read.csv("data/raw/TRY/TRY_Categorical_Traits_Lookup_Table_2012_03_17_TestRelease.csv",
+         stringsAsFactors=FALSE,na.strings = "")
+Pheno.Zanne <- read.csv("data/raw/ZanneNature/GlobalLeafPhenologyDatabase.csv",
+         stringsAsFactors=FALSE)
+# extract
+data.cat.extract <- do.call("rbind",lapply(data.traits$sp ,fun.get.cat.var.from.try,
+                                           data.traits,try.cat,Pheno.Zanne))
+# change category
+data.cat.extract <- fun.change.factor.pheno.try(data.cat.extract)
+data.cat.extract <- fun.change.factor.angio.try(data.cat.extract)
+data.cat.extract <- fun.fill.pheno.try.with.zanne(data.cat.extract)
+
+data.traits <- merge(data.traits,data.cat.extract[,c("sp","Phylo.group","Pheno.T")],by="sp")
+
 ### Export
 write.csv(data.traits,file="output/formatted/Mbaiki/traits.csv",row.names = FALSE)
 

R/find.trait/NSW.R

@@ -33,6 +33,25 @@ rm(data.trait)
 ## extract
 data.traits <- fun.extract.format.sp.traits.NOT.TRY(sp=species.clean$sp, Latin_name=species.clean$Latin_name, data=data.TRAITS.std,name.match.traits="sp")
 
+
+#### GET THE ANGIO/CONIF AND EVERGREEN/DECIDUOUS
+# read try categrocial data
+try.cat <- read.csv("data/raw/TRY/TRY_Categorical_Traits_Lookup_Table_2012_03_17_TestRelease.csv",
+         stringsAsFactors=FALSE,na.strings = "")
+Pheno.Zanne <- read.csv("data/raw/ZanneNature/GlobalLeafPhenologyDatabase.csv",
+         stringsAsFactors=FALSE)
+# extract
+data.cat.extract <- do.call("rbind",lapply(data.traits$sp ,fun.get.cat.var.from.try,
+                                           data.traits,try.cat,Pheno.Zanne))
+# change category
+data.cat.extract <- fun.change.factor.pheno.try(data.cat.extract)
+data.cat.extract <- fun.change.factor.angio.try(data.cat.extract)
+data.cat.extract <- fun.fill.pheno.try.with.zanne(data.cat.extract)
+
+
+data.traits <- merge(data.traits,data.cat.extract[,c("sp","Phylo.group","Pheno.T")],by="sp")
+
+
 ### TODO ADD GENUS MEAN FOR HEIGHT IF SPECIES IS MISSING
 write.csv(data.traits,file="output/formatted/NSW/traits.csv",row.names = FALSE)
 

R/find.trait/NVS.R

@@ -31,8 +31,48 @@ data.trait$Wood.density.sd <- NA
 data.trait$Max.height.mean <- data.trait$height.m; data.trait$height.m <- NULL
 data.trait$Max.height.sd <- NA
 
-## read traits from TRY
+## read traits from data
 data.traits <- fun.extract.format.sp.traits.NOT.TRY(sp=species.clean$sp, Latin_name=species.clean$Latin_name, data=data.trait,name.match.traits="Latin_name")
 
+## TODO GET ANGIO CONIF DECIDUOUS EVERGREEN BUT NEED SPECIES LATIN NAME
+NVS.SPECIES.name <- read.csv("data/raw/NVS/CurrentNVSNames.csv",sep=';', stringsAsFactors = FALSE)
+species.clean$Latin_name <- NVS.SPECIES.name$Species.Name[match(species.clean$Latin_name_syn,
+                                                                NVS.SPECIES.name$NVS.Code)]
+data.traits$Latin_name <- species.clean$Latin_name
+
+#### GET THE ANGIO/CONIF AND EVERGREEN/DECIDUOUS
+
+## FOR NEW ZEALADN BETTER TO FOLLOW  McGlone et al. 2004. Winter leaf loss in the New Zealand woody flora. New Zealand Journal of Botany, 2004, Vol. 42: 1-19. which report 11 species asdeciduous adn 11 species as semi-deciduous
+# read try categrocial data
+try.cat <- read.csv("data/raw/TRY/TRY_Categorical_Traits_Lookup_Table_2012_03_17_TestRelease.csv",
+         stringsAsFactors=FALSE,na.strings = "")
+Pheno.Zanne <- read.csv("data/raw/ZanneNature/GlobalLeafPhenologyDatabase.csv",
+         stringsAsFactors=FALSE)
+# extract
+data.cat.extract <- do.call("rbind",lapply(data.traits$sp ,fun.get.cat.var.from.try,
+                                           data.traits,try.cat,Pheno.Zanne))
+# change category
+data.cat.extract <- fun.change.factor.pheno.try(data.cat.extract)
+data.cat.extract <- fun.change.factor.angio.try(data.cat.extract)
+data.cat.extract <- fun.fill.pheno.try.with.zanne(data.cat.extract)
+
+## FOR NEW ZEALAND BETTER TO FOLLOW  McGlone et al. 2004. Winter leaf loss in the New Zealand woody flora. New Zealand Journal of Botany, 2004, Vol. 42: 1-19. which report 11 species asdeciduous adn 11 species as semi-deciduous
+
+## according to McGlone et al. 2004. Winter leaf loss in the New Zealand woody flora. New Zealand Journal of Botany, 2004, Vol. 42: 1-19. all other species are evergreen
+data.cat.extract[,'Pheno.T'] <- 'EV'
+
+data.cat.extract[data.cat.extract$Latin_name %in% c('Discaria toumatou',
+'Fuchsia excorticata','Hoheria glabrata','Hoheria lyallii',
+'Muehlenbeckia astonii','Olearia fragantissima','Olearia gardneri','Olearia hectori',
+'Olearia odorata','Plagianthus divaricatus','Plagianthus regius'),'Pheno.T'] <- 'D'
+
+data.cat.extract[data.cat.extract$Latin_name %in% c('Aristotelia serrata',
+'Carmichaelia odorata','Carmichaelia arborea',
+'Coprosma virescens','Coriaria arborea var. arborea','Fuchsia perscandens',
+'Fuchsia procumbens','Muehlenbeckia australis','Muehlenbeckia complexa',
+'Olearia fimbriata','Urtica ferox'),'Pheno.T'] <- 'D_EV'
+
+data.traits <- merge(data.traits,data.cat.extract[,c("sp","Phylo.group","Pheno.T")],by="sp")
+
 ### TODO ADD GENUS MEAN FOR HEIGHT IF SPECIES IS MISSING
 write.csv(data.traits,file="output/formatted/NVS/traits.csv",row.names = FALSE)

R/find.trait/Paracou.R

@@ -314,6 +314,24 @@ species.clean2 <- data.frame(sp=data.tree[!duplicated(data.tree[["sp"]]),"sp"],
 data.traits <- fun.extract.format.sp.traits.NOT.TRY(sp=species.clean2$sp, Latin_name=species.clean2$Latin_name, data=data.species,name.match.traits="Latin_name")
 
 
+#### GET THE ANGIO/CONIF AND EVERGREEN/DECIDUOUS
+# read try categrocial data
+try.cat <- read.csv("data/raw/TRY/TRY_Categorical_Traits_Lookup_Table_2012_03_17_TestRelease.csv",
+         stringsAsFactors=FALSE,na.strings = "")
+Pheno.Zanne <- read.csv("data/raw/ZanneNature/GlobalLeafPhenologyDatabase.csv",
+         stringsAsFactors=FALSE)
+# extract
+data.cat.extract <- do.call("rbind",lapply(data.traits$sp ,fun.get.cat.var.from.try,
+                                           data.traits,try.cat,Pheno.Zanne))
+# change category
+data.cat.extract <- fun.change.factor.pheno.try(data.cat.extract)
+data.cat.extract <- fun.change.factor.angio.try(data.cat.extract)
+data.cat.extract <- fun.fill.pheno.try.with.zanne(data.cat.extract)
+
+
+data.traits <- merge(data.traits,data.cat.extract[,c("sp","Phylo.group","Pheno.T")],by="sp")
+
+
 # write.table(data.genus,file="data.genus.txt",sep="\t",row.names=FALSE)
 write.csv(data.traits,file="./output/formatted/Paracou/traits.csv",row.names=FALSE)
 

R/find.trait/Spain.R

@@ -22,14 +22,48 @@ max.height <- read.csv(file="output/formatted/Spain/max.height.csv", stringsAsFa
 max.height$sp <- paste("sp",max.height$sp,sep=".")
 
 ## extract traits and height
-data.traits <- fun.extract.format.sp.traits.TRY(sp=species.clean[["sp"]],sp.syno.table=species.clean,data=data.TRY.std)
-data.traits <- merge(data.traits,subset(max.height,select=c("sp","Max.height.mean","Max.height.sd")),by="sp",all.x=TRUE,all.y=FALSE)
+data.traits <- fun.extract.format.sp.traits.TRY(sp=species.clean[["sp"]],
+                                                sp.syno.table=species.clean,
+                                                data=data.TRY.std)
+data.traits <- merge(data.traits,subset(max.height,select=c("sp","Max.height.mean","Max.height.sd")),
+                     by="sp",all.x=TRUE,all.y=FALSE)
 data.traits$Max.height.genus <- FALSE
 # genus mean for height
-height.genus.DF <- do.call("rbind",lapply(data.traits$Latin_name,fun.compute.mean.genus,data.traits,"Max.height.mean"))
+height.genus.DF <- do.call("rbind",lapply(data.traits$Latin_name,
+                                          fun.compute.mean.genus,data.traits,"Max.height.mean"))
 data.traits[is.na(data.traits[["Max.height.mean"]]),
-            c("Max.height.mean","Max.height.sd","Max.height.genus")] <- height.genus.DF[is.na(data.traits[["Max.height.mean"]]),]
+            c("Max.height.mean","Max.height.sd","Max.height.genus")] <-
+    height.genus.DF[is.na(data.traits[["Max.height.mean"]]),]
 
-### TODO ADD GENUS MEAN FOR HEIGHT IF SPECIES IS MISSING
+
+#### GET THE ANGIO/CONIF AND EVERGREEN/DECIDUOUS
+# read try categrocial data
+try.cat <- read.csv("data/raw/TRY/TRY_Categorical_Traits_Lookup_Table_2012_03_17_TestRelease.csv",
+         stringsAsFactors=FALSE,na.strings = "")
+Pheno.Zanne <- read.csv("data/raw/ZanneNature/GlobalLeafPhenologyDatabase.csv",
+         stringsAsFactors=FALSE)
+# extract
+data.cat.extract <- do.call("rbind",lapply(data.traits$sp ,fun.get.cat.var.from.try,
+                                           data.traits,try.cat,Pheno.Zanne))
+# change category
+data.cat.extract <- fun.change.factor.pheno.try(data.cat.extract)
+data.cat.extract <- fun.change.factor.angio.try(data.cat.extract)
+data.cat.extract <- fun.fill.pheno.try.with.zanne(data.cat.extract)
+
+## fix pheno for species with issue
+data.cat.extract[data.cat.extract$Latin_name %in% c('Crataegus spp.','Crataegus laciniata',
+                                                    'Pyrus spp.','Morus spp.','Salix spp.',
+                                                    'Betula spp.','Salix elaegnos',
+                                                    'Tilia spp.','Sorbus spp.',
+                                                    'Prunus spp.','Larix spp.'),'Pheno.T'] <- 'D'
+
+data.cat.extract[data.cat.extract$Latin_name %in% c('Juniperus turbinata',
+                                                    'Otros pinos'),'Pheno.T']<-  'EV'
+
+
+
+data.traits <- merge(data.traits,data.cat.extract[,c("sp","Phylo.group","Pheno.T")],by="sp")
+
+# write
 write.csv(data.traits,file="output/formatted/Spain/traits.csv",row.names = FALSE)
 

R/find.trait/Sweden.R

@@ -80,7 +80,31 @@ data.traits$SLA.genus[data.traits$sp=="sp.51"] <- FALSE
 data.traits$Wood.density.genus[data.traits$sp=="sp.51"] <- FALSE
 data.traits$Max.height.genus[data.traits$sp=="sp.51"] <- FALSE
 
-### TODO ADD GENUS MEAN FOR HEIGHT IF SPECIES IS MISSING
+#### GET THE ANGIO/CONIF AND EVERGREEN/DECIDUOUS
+# read try categrocial data
+try.cat <- read.csv("data/raw/TRY/TRY_Categorical_Traits_Lookup_Table_2012_03_17_TestRelease.csv",
+         stringsAsFactors=FALSE,na.strings = "")
+Pheno.Zanne <- read.csv("data/raw/ZanneNature/GlobalLeafPhenologyDatabase.csv",
+         stringsAsFactors=FALSE)
+# extract
+data.cat.extract <- do.call("rbind",lapply(data.traits$sp ,fun.get.cat.var.from.try,
+                                           data.traits,try.cat,Pheno.Zanne))
+# change category
+data.cat.extract <- fun.change.factor.pheno.try(data.cat.extract)
+data.cat.extract <- fun.change.factor.angio.try(data.cat.extract)
+data.cat.extract <- fun.fill.pheno.try.with.zanne(data.cat.extract)
+
+## fix pheno for species with issue
+data.cat.extract[data.cat.extract$Latin_name %in% c('Betula ssp','Quercus robur_petraea',
+    'Ulmus ssp'),'Pheno.T'] <- 'D'
+
+data.cat.extract[data.cat.extract$Latin_name %in% c('Abies ssp',
+       'Picea ssp other than P.abies') ,'Pheno.T']<-  'EV'
+
+
+data.traits <- merge(data.traits,data.cat.extract[,c("sp","Phylo.group","Pheno.T")],by="sp")
+
+### writing
 write.csv(data.traits,file="output/formatted/Sweden/traits.csv",row.names = FALSE)